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This paper is in the following e-collection/theme issue:

Quality Improvement (366) E-Health Policy and Health Systems Innovation (512) Public (e)Health, Digital Epidemiology and Public Health Informatics (2250) Design and Usability of Clinical Software and EHRs (453) Artificial Intelligence (4620) Security in Digital Health (79) Medical Device Adverse Events, Errors, Safety (36) Generative Language Models Including ChatGPT (1451)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/94846, first published .
Cybersecurity experts analyze AI-enabled medical device threat map and network segmentation strategies.

Regulatory Approaches to Cybersecurity Risk Management for AI-Enabled Medical Device Software in Korea, the United States, and the European Union: Comparative Document Analysis

Regulatory Approaches to Cybersecurity Risk Management for AI-Enabled Medical Device Software in Korea, the United States, and the European Union: Comparative Document Analysis

Authors of this article:

Saera Jung1, 2 Author Orcid Image ;   Kihong Son1, 3 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Saera Jung   1, 2 , MS ;   Kihong Son   1, 3 , PhD

1 Department of Artificial Intelligence, University of Science and Technology (UST), Daejeon, Republic of Korea

2 Qualitics Consulting, Seoul, Republic of Korea

3 Medical Information Research Section, Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea

Corresponding Author:

  • Kihong Son, PhD
  • Department of Artificial Intelligence
  • University of Science and Technology (UST)
  • 217 Gajeong-ro, Yuseong District
  • Daejeon
  • Republic of Korea
  • Phone: 82 10-8633-1544
  • Email: kihong@etri.re.kr